Service-Centric Approach to AIOps

January 10, 2019

Operations teams are undergoing a paradigm shift and embracing big data, modern machine learning, and other advanced analytics technologies to boost operations efficiency with proactive, personal, and dynamic insight. Gartner has coined the term AIOps (artificial intelligence for IT operations) to capture the spirit of these changes. Current methodologies, techniques, and best practices are shackled by traditional siloed Operations Support System (OSS) stacks, rigid rule-based systems, and monolithic architectures. AIOps helps to quickly extract actionable insights from the operational data to help automate tasks and processes that have traditionally required human intervention.

Spotlight

Pepperdata

Pepperdata is the Big Data performance company. Leading companies such as Comcast, Philips Wellcentive, and Zillow depend on Pepperdata to manage and improve the performance of Hadoop and Spark. Enterprise customers use Pepperdata products and services to troubleshoot performance problems in production, increase cluster utilization, and enforce policies to support multi-tenancy. Pepperdata products and services work with customer Big Data systems both on-premise and in the cloud.

OTHER WHITEPAPERS
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Introducing Apache Druid

whitePaper | January 31, 2020

Many companies have invested heavily in specialized enterprise data warehouses (EDW) and Extract, Transform and Load (ETL) technologies to analyze their operational data. But these technologies were never designed to be truly real-time.They were originally built for batch, and that original design limits how real-timeEDWs and ETL can become. They were also designed to support a focused group ofanalysts, not a larger group of employees spanning operational functions, or even partner and end customers.

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Enterprise Data Orchestration

whitePaper | June 3, 2021

Data growth continues at an exponential rate even as cloud architectures make data management more complex and advanced applications necessitate more data movement. So what can be done to enable clean data capture and movement across an enterprise? Read this white paper to learn the requirements for data orchestration at scale and discover how you can build a holistic data architecture that enables successful DataOps.

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How to Analyze and Maximize Customer Retention: Asset

whitePaper | May 10, 2022

Understanding all the factors that impact customer health and retention requires a comprehensive view of complex data.

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On Artificial Intelligence A European approach to excellence and trust

whitePaper | February 19, 2020

Artificial Intelligence is developing fast. It will change our lives by improving healthcare (e.g. making diagnosis more precise, enabling better prevention of diseases), increasing the efficiency of farming, contributing to climate change mitigation and adaptation, improving the efficiency of production systems through predictive maintenance, increasing the security of Europeans, and in many other ways that we can only begin to imagine. At the same time, Artificial Intelligence (AI) entails a number of potential risks, such as opaque decision-making, gender-based or other kinds of discrimination, intrusion in our private lives or being used for criminal purposes.

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Four Reasons Your Metadata Is Broken

whitePaper | April 1, 2021

Metadata is more important now than ever. New technologies have enabled businesspeople who have traditionally not been analysts to work with data. The consumerization of IT means people expect systems to be intuitive and require little training. With so many people using data to support so many kinds of decisions, it’s critical that your data is described, defined, and understood.

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The Value of Oracle Enterprise Manager for Managing Oracle Databases

whitePaper | February 7, 2020

Multiple studies have proven that, while the business demand for databases grows, operational teams are constrained by traditional, reactive processes. Combined with budgetary pressures, this causes them to fall short in meeting the demand in a timely fashion. In addition, as companies adopt cloud paradigms, operational teams must manage across on-premises and cloud environments with the same resources. To be effective, companies need to shift from a reactive posture to one of standardization and proactive analysis and planning by leveraging intuitive tooling to automate manually intensive and non-value adding activities and to deliver real-time insights.

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Spotlight

Pepperdata

Pepperdata is the Big Data performance company. Leading companies such as Comcast, Philips Wellcentive, and Zillow depend on Pepperdata to manage and improve the performance of Hadoop and Spark. Enterprise customers use Pepperdata products and services to troubleshoot performance problems in production, increase cluster utilization, and enforce policies to support multi-tenancy. Pepperdata products and services work with customer Big Data systems both on-premise and in the cloud.

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